Title page for ETD etd-04212006-161144


Type of Document Master's Thesis
Author Sarvaiya, Hetal Abhijeet
URN etd-04212006-161144
Title Mass Spectrometric Characterization of the MCF7 Cancer Cell Line: Proteome Profile and Cancer Biomarkers
Degree Master of Science
Department Biomedical Engineering and Sciences
Advisory Committee
Advisor Name Title
Lazar, Iuliana M. Committee Chair
Lee, Yong Woo Committee Member
Love, Brian J. Committee Member
Keywords
  • Mass spectrometry
  • Cancer
  • Biomarkers
  • Proteomics
  • MCF7
  • Microfluidics
Date of Defense 2006-04-18
Availability restricted
Abstract
The discovery of cancer biomarkers is crucial in the clinical setting to facilitate early diagnosis and treatment, thereby increasing survival rates. Proteomic technologies with mass spectrometry detection (MS) have the potential to affect the entire spectrum of cancer research by identifying these biomarkers. Simultaneously, microfabricated devices have evolved into ideal analysis platforms for minute amounts of sample, with promising applications for proteomic investigations and future biomarker screening. This thesis reports on the analysis of the proteomic constituents of the MCF7 breast cancer cell line using a shotgun 2-D strong cationic exchange/reversed phase liquid chromatography electrospray ionization tandem mass spectrometry (SCX/RP-LC-ESI-MS/MS) protocol. A series of optimization strategies were performed to improve the LC-MS experimental set-up, sample preparation, data acquisition and database searching parameters, and to enable the detection and confident identification of a large number of proteins. Over ~4,500 proteins were identified using conventional filtering parameters, and >2000 proteins using a combination of filters and p-value sorting. Of these, ~1,950 proteins had p<0.001 (~90%) and more than half were identified by ≥ 2 unique peptides. About 220 proteins were functionally involved in cancer related cellular processes, and over 100 proteins were previously described in the literature as potential cancer markers. Biomarkers such as PCNA, cathepsin D, E-cadherin, 14-3-3-sigma, antigen Ki-67, TP53RK, and calreticulin were identified. These data were generated by subjecting to mass spectrometric analysis ~42 µg of protein digest, analyzing 16 SCX peptide fractions, and interpreting ~55,000 MS2 spectra. Total MS time required for analysis was 40 h.

Selective SCX fractions were also analyzed by using a microfluidic LC platform. The performance of the microchip LC was comparable to that obtained with bench-top instrumentation when similar experimental conditions were used. The identification of 5 cancer biomarkers was enabled by using the microchip LC platform. Furthermore, this device was also capable to analyze phosphopeptides.

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